As explained in section 2.3.3, four “typical” microstates were extracted from the LR group in the time window between -200 and 794 ms in the FD condition. Their topographic maps and temporal sequence can be seen Figure 2.13. To test whether attention engagement to the stimulus was atypical in infants with emerging ASD, I selected the microstate map M4, whose spatial configuration and temporal profile of the scalp potential field correspond to the Nc (central negative deflection after 300 ms from the stimulus onset). Thus, M4 was identified in the three HR groups data between 300 and 794 ms in all stimuli conditions. The difference in duration of M4 between FD and Noise varied by HR outcome group (F(2,75)=3.39, p=0.039, h2= 0.083, Table A2.16, Figure A2.4b); the difference in mean GFP, representing the strength of the scalp field, did not (F(2,72)=0.40, p=0.672, h2= 0.011, Table A2.15, Figure A2.4a). Post-hoc comparisons of FD-Noise difference scores indicated that the HR-ASD group spent significantly less time than HR-Aty in M4 when attending the FD than to the Noise condition (Tukey post-hoc test, p=0.036, see Figure 2.14a); other comparisons between groups were not significant (HR-
ms -10 0 0 100 200 30 0 40 0 500 60 0 700 ms -100 0 100 200 300 400 500 600 700 ms -100 0 100 200 300 400 500 600 700 ms -100 0 100 200 300 400 500 600 700 ms -10 0 0 100 200 30 0 40 0 500 60 0 700 ms -100 0 100 200 300 400 500 600 700 ms -100 0 100 200 300 400 500 600 700 ms -100 0 100 200 300 400 500 600 700
Face with Averted Gaze Noise Face with Direct Gaze
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TD versus HR-Aty: p=0.531, HR-TD versus HR-ASD: p=0.144). Socialisation scores at 3 years were significantly predicted by difference in mean GFP of M4 between the FD and Noise condition (b=20.94, t(73)=2.111, p=0.039, Table A2.17, Figure 2.14b) but not in duration (b=-0.005, t(74)=- 0.29, p=0.77, Table A2.19). Of note, FD-Noise difference in mean GFP of M4 did not significantly predict later non-social adaptive skills (b=10.85, t(73)= 1.15, p=0.25, Table A2.18).
MANOVA assessing differences between conditions in the LR group showed no such effect in mean Global Field Power (GFP, F(1,35)=1.672, p=0.204, h2=0.046) and duration (F(1,36)=0.249, p=0.621, h2=0.017). Microstates were different in terms of their GFP (F(2,34)=4.392, p=0.020, h2=0.205) and nearly so in their duration (F(2,35)=3.101, p=0.058, h2=0.151). Post-hoc pairwise comparisons with Bonferroni adjustment for multiple testing revealed that mean GFP of M4 and, to a lesser extent, M1 was higher than M2 (p=0.007 and p=0.067, respectively). However, there was no difference in mean GFP between M1 and M4 (p=1) nor in duration of the microstates (all ps =1 in post-hoc comparisons). The latter result provided suggestive evidence for the fact that microstate maps extracted in the FD condition had a good fit on the Noise data too. This aspect could be considered a confirmation of the fact that they were indeed reflecting underlying general attentional processes in the LR group. All results can be seen in the Appendix of this chapter (Tables A2.20,A2.21, Figure A2.7).
In the MANOVA testing for an interaction effect between condition and outcome group, I found no significant effect of outcome in mean GFP (F(2,80)=2.374, p=0.100, h2=0.056) and duration (F(2,85)=1.675, p=0.193, h2=0.038) of the three microstates. Mean GFP appeared to be higher in the FD than in the Noise condition overall (F(1,80)=5.938, p=0.017, h2=0.069), with no significant interaction between condition and outcome group (F(2,80)=0.882, p=0.418, h2=0.022). There was no difference in duration between the two conditions (F(1,85)=5.938, p=0.424, h2=0.008) and the interaction between condition and outcome was non-significant (F(2,85)=0.882, p=0.061, h2=0.064). Post-hoc investigations of this effect through separate ANOVAs for each microstate revealed that this effect did not emerge as significant in any of the microstates (all ps>0.121). Of interest, microstates features were not influenced by age, sex or Phase (see Tables A2.22, A2.23 for all results of the HR group MANOVAs).
Thus, overall HR outcome groups were not different in terms of microstate features. This result is reassuring with respect to the possible bias that would have occurred if the microstate maps, tuned on the FD data, fitted the data better in the FD condition (if significantly longer durations of the microstates were observed in the FD compared to the Noise condition).
Figure 2.13 The “typical” microstates during social attention. a Scalp field topography of the four optimal microstate maps estimated from the Low-Risk (LR) infants in the Face with Direct Gaze condition. Global Field Power (GFP) in the microstate ranges from -3.5 (blue) to 3.5 (red) microVolts. b Sequence of microstates in the Face with Direct Gaze between -200 and 794 milliseconds (on the x- axis). The blue area indicates that the topography of the scalp field reflects microstate map 1 (M1), green reflects microstate map 2 (M2), red reflects microstate map 3 (M3) while cyan reflects microstate map 4 (M4). On the y-axis, absolute values of the mean GFP for each time-stamp, in microVolts, are indicated.
Figure 2.14 Microstate 4 in relation to outcome. a Mean microstate 4 (M4) duration, in milliseconds, in the Face with Direct Gaze (represented by rhombuses) and Noise (represented by squares) conditions for the four outcome groups. Bars represent ± standard error. b Scatterplot representing the relationship between M4 mean Global Field Power (GFP) difference between the FD and Noise conditions at 8 months (in microVolts), on the x-axis, and VABS Soc. at 3 years on the y-axis in the three high-risk groups. The regression line for the entire group of HR infants is displayed as a black line, with grey shadows representing standard errors.
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